2016 UMKC Dissertations - Access Restricted to UMKC
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Item The effects of HIV-1 viral protein r (vpr) and anti-retroviral drugs in the brain: Implications in HIV-1 associated neurocognitive disorders(University of Missouri--Kansas City, 2016) Gangwani, Mohitkumar R.; Kumar, AnilThe morbidity and mortality of HIV-1 infected individuals has declined significantly by the introduction of highly active antiretroviral therapy (HAART). Nevertheless, different forms of HIV-1 associated neurocognitive disorders (HAND) still persist and affect about half of the HIV infected population. The importance of HIV-1 accessory protein Vpr has been well established in the pathology of AIDS in the peripheral and central nervous system. However, the role of Vpr in neuroinflammation and the underlying mechanisms involved have not been extensively studied. The RNA/Protein expression levels of three cytokines/chemokines (IL-6, IL-8 and CCL5) in the Vpr expressing astrocytes were determined in our study. We also examined the cellular mechanisms responsible for the Vpr-mediated induction of IL-6, IL-8 and CCL5. Recently, it has been noted that long term use of HAART and its associated toxicity might be involved in the persistence of HAND in HAART era. We studied the effects of antiretroviral drugs in vitro in astrocytes and neurons and in vivo in mice. We found that antiretroviral drugs lopinavir/ritonavir produce neuroinflammatory cytokines/chemokines (IL 6 and IL-8) and oxidative stress in vitro. Neuroplasticity proteins and antioxidant system were also perturbed by lopinavir/ritonavir treatment in mice brain which were prevented by the pretreatment with sulforaphane. In the first chapter, we investigate the effect of Vpr on the induction of IL-6 and IL-8 in human astrocytes. The levels of IL-6 and IL-8 showed significant increase both in primary human fetal astrocytes and in SVG astrocytic cell line transfected with a Vpr-expressing plasmid. Also, the involvements of PI3K-Akt and p38MAPK pathways as well as the transcription factor NF-κB, C/EBP and AP-1 were determined in Vpr-mediated induction of IL-6 and IL-8 by utilization of chemical inhibitors and siRNAs. In additional experiments, the translocation of NF-κB subunit p65 and the phosphorylation levels of various signaling molecules triggered by Vpr were determined. In the second chapter, the effect of Vpr on CCL5 induction was investigated in astrocytes. The expression levels of CCL5 showed significant up-regulation induced by Vpr. Moreover, the involvements of PI3K-Akt and p38MAPK pathways as well as the transcription factors NF-κB and AP-1 were determined in Vpr-mediated induction of CCL5 in astrocytes. In the third chapter, we investigate the effects of protease inhibitor drugs on the memory dysfunction. Proinflammatory cytokines/chemokines IL-6 and IL-8 showed significant up-regulation by lopinavir/ritonavir treatment in human fetal astrocytes and SVG astrocytic cell line. Reactive oxygen species was increased by lopinavir/ritonavir treatment in human fetal astrocytes, SVG astrocytes and differentiated SH-SY5Y neuronal cells. Lopinavir/ritonavir treatment caused significant learning and memory dysfunction in mice accompanied by the development of anxiety like phenomenon. Synaptic neuroplasticity genes, neurotropic factors and antioxidant genes were compromised by lopinavir/ritonavir treatment in mice brain. Neuroprotective plant isothiocynate compound sulforaphane rescued memory dysfunction caused by lopinavir/ritonavir and increased the levels of synaptic neuroplasticity genes, neurotropic factors and antioxidant genes. In conclusion, we demonstrated that HIV-1 Vpr was able to increase the production of pro-inflammatory cytokine/chemokines IL-6, IL-8 and CCL5 via different pathways. We demonstrated that lopinavir/ritonavir is involved in the development of HAND by inducing IL-6, IL-8, ROS and reducing antioxidant genes, neurotropic factors and synaptic plasticity proteins. We also showed that sulforaphane pretreatment was protective in lopinavir/ritonavir treated mice. The underlying mechanisms provide possible therapeutic targets for the intervention of neurocognitive dysfunction in HAND.Item Essays on Complexity and Design Thinking in Entrepreneurship(University of Missouri--Kansas City, 2016) Sarooghi, Hessamoddin; Hornsby, Jeffrey S. (Jeffrey Scott), 1959-The New venture creation context is experiencing unprecedented change. Rapid shifts in technology, customer needs, and institutions have translated into a very complex, uncertain, and dynamic landscape, for those who want to embark on an entrepreneurial journey. Success in this turbulent environment requires entrepreneurs to be equipped with the mindsets, processes, and tools that help them to systematically overcome and diminish the inherent complexity of the entrepreneurship pathway. In the first essay of this dissertation, we formally incorporate the notion of complexity into the current debates on entrepreneurial opportunities. More specifically, we propose a new conceptualization of opportunity heterogeneity that attributes the variance in opportunities to complexity in three constituent components; problem, solution, and business model. Utilizing this complexity perspective, we revisit the impact of creativity, prior knowledge and social ties on the process of identifying entrepreneurial opportunities. In the second essay, through a systematic scale development process, we conceptualize and quantify design thinking as a complexity-reducing mindset that is activated in problem-solving situations. Particularly, we measure design thinking as a Reflective First-order, Formative Second-order construct through three facets; visual thinking, empathy, and experimentation. Subsequently, we assess the validity and reliability of our proposed design thinking construct. The insights from this dissertation have important implications for both theory and practice and facilitate future research inquiries in multiple scholarly domains.Item Simulating Urban Landscape Transformation: Implications for Urban Wetlands at Multiple Scales(University of Missouri--Kansas City, 2016) Zubair, Opeyemi A.; Ji, Wei, 1955-Urban landscape change simulation has received increasing attention in recent times. As a result, many studies have focused on various aspects of land change simulation, ranging from uncertainty of input data to model accuracy. While efforts have been put into improving many of the existing urban land change models and developing new ones, not so much has been done in understanding the significance of methods of classifying the satellite images often used as input maps in many of these models. In addition, few studies have been done to assess the impact of modeled landscapes on surrounding natural ecosystems such as urban wetlands, which have served as sensitive indicator of both human impacts and climate variation. In this study, the aim was to simulate the change in Kansas City landscape, and to assess the impact of the change on wetlands at various spatial scales within the study area. To achieve this, the study was divided into three parts. The first part examined how significant the impacts of classification methods of input land cover maps are on the overall accuracy of the urban land change prediction used in this study. This was done by classifying the historical SPOT satellite images of Kansas City using multi-layer perceptron neural network and maximum likelihood classification techniques. The impact of these two classification methods on the overall accuracy of land change prediction was assessed. The study made use of the classified map of a known year and other historical high-resolution satellite data of the study area from Google Earth to validate results from both predictions. The result from this first part shows that the methods selected in classifying satellite images often used as input in many land change models can significantly affect land change prediction. In the second and third parts, two model methods (Similarity Weighted Instance-based Machine Learning - SimWeight and Multi-layer Perceptron Neural Network - MLP) were compared to determine which is most appropriate for use in this study. To achieve this, the study utilized an integrated approach that combined Similarity Weighted Instance-based Machine Learning and Markov model in one approach and Multi-layer Perceptron Neural Network and Markov chain in a second approach. These two methods were used in simulating the landscape change of three major watersheds in the Kansas City area into a known year. The model that performed best was used in simulating into the future and the impact of change was assessed on wetlands at different scales. In order to achieve this, classified SPOT satellite data covering the three major watersheds were used to generate the historical land cover data series between 1992 and 2010. In addition, the study identified several land change variables associated with the historical change process in the study area. These variables together with the result of the historical land change between 1992 and 2010 were used in modeling urban landscape transformation into an end date of 2014 for both model methods assessed. A Markov model was applied to perform these predictions. The prediction results were verified with a more accurate map that was derived from independently classifying a 2014 SPOT image of the study area. Accuracy assessments for the 2014 predicted maps and the independently classified map of 2014 were compared. Based on a higher accuracy result obtained for the SimWeight approach, prediction into an end date of 2028 was made. The historical impact of human-induced landscape change on wetlands between 1992 & 2010 and the potential impact by 2028 were assessed for the study area. This integrated modeling approach in combination with land change driving variables provided valuable insights about how the landscape of the three major watersheds may develop in the future, and how this development may affect urban wetlands in the study area.Item Application of Ab Initio Calculations and Molecular Dynamics to Collagen and Brome Mosaic Virus(University of Missouri--Kansas City, 2016) Eifler, Jay Q.; Ching, Wai-YimMolecular Dynamics (MD) simulations are no more accurate than the underlying force field which represents the molecular interactions. In this thesis, we have calculated ab initio atomic partial charges for proteins of collagen and the brome mosaic virus (BMV) capsid. These proteins contain from 1000-3000 atoms and efficient and accurate ab initio quantum modeling methods have only become more recently available for systems of this size. We have used our own in-house quantum modeling package: the Orthogonalized Linear Combination of Atomic Orbitals (OLCAO) for calculating ab initio atomic partial charges and Nanoscale Molecular Dynamics (NAMD) as a MD engine. We first examine the charge and bonding for proteins of collagen and BMV using a simplified method based on amino acids as a structural unit of proteins and secondly using fully self-consistent field (scf) calculations. We find that the charge and bonding properties of amino acids are significantly altered by their environment within the protein and by surrounding solvent but can be modeled accurately with an amino acid method or fully scf calculation. Both amino acid method and scf partial charges are used as input into NAMD for MD simulation with the purpose of comparing the default NAMD partial charges and the protein-specific partial charges of OLCAO. We find that both NAMD and OLCAO partial charges produce MD simulations that can equilibrate to similar structures as measured by root-mean-square-deviation (RMSD) of coordinates relative to the starting structure and radius of gyration (Rg) of coordinates but that differences still exist in the trajectories and details of the structures. We conclude that more system specific charge parameters are necessary for larger proteins to accurately model the MD trajectory than can be provided for by charge parameters derived from model peptides as used in the NAMD charge parameters.Item The Effect of Drugs of Abuse and HIV-1 GP120 on Autophagy in Astrocytes(University of Missouri--Kansas City, 2016) Cao, Lu; Kumar, AnilThe life expectancy of individuals infected with HIV-1 has significantly improved since the introduction of highly active anti-retroviral therapy (HAART). However, this has led to an increase in the prevalence of HIV-associated neurocognitive disorders (HAND), especially the mild forms of HAND. Drugs of abuse are known to exacerbate neuropathological dysfunction in HIV-infected individuals. The neuropathological manifestation results from cell death in the CNS wherein autophagy is expected to play an important role. Autophagy is generally considered protective during deprivation or stress. However, excessive autophagy can be destructive, leading to autophagic cell death. The present study was based on the central hypothesis that drugs of abuse and HIV-1 viral proteins work synergistically in mediating autophagy in human astrocytes. The level of autophagy mediated by cocaine, methamphetamine, and HIV-1 gp120 is determined. Furthermore, we examined the cellular mechanisms responsible for cocaine and methamphetamine-mediated autophagy pathway, and the role of autophagy in drug-induced cytotoxicity. In the first chapter, we investigate the effect of cocaine on autophagy in SVGA astrocytes. We measured levels of the autophagic marker protein LC3II in SVGA astrocytes after exposure with cocaine. The results showed that cocaine caused an increase in LC3II level in a dose- and time-dependent manner. This result was also confirmed by detecting LC3II in SVGA astrocytes using confocal microscopy and transmission electron microscopy. Next, we sought to explore the mechanism by which cocaine induces the autophagic response. The involvement of sigma 1 receptor, and autophagy signaling proteins p-mTOR, Atg5, Atg7, and p-Bcl-2/Beclin-1 were determined by using selective inhibitors and siRNAs. In addition, we determined the role of autophagy in chronic cocaine exposure using MTT assay and western blot analysis. In the second chapter, the effect of methamphetamine on autophagy in SVGA astrocytes, as well as human fetal astrocytes were examined. The mechanistic pathway of methamphetamine-mediated autophagy was determined. In the third chapter, the synergistic effect of methamphetamine and HIV-1 gp120 IIIb on autophagy in SVGA astrocytic cell line and human astrocytes was determined. The signaling mechanism of methamphetamine- and gp120- mediated autophagy is investigated by utilization of specific inhibitors and siRNAs. Furthermore, the role of autophagy during methamphetamine- and gp120- induced cytotoxicity is examined by MTT assay and PI staining. In conclusion, we showed that drugs of abuse and HIV-1 viral protein gp120 were able to induce autophagy in astrocytes. The underlying mechanism provides potential therapeutic target for neuroAIDS.